Models to Simulate Effective Coverage of Fire Station Based on Real-Time Travel Times

In recent years,frequent fire disasters have led to enormous damage in China.Effective firefighting rescues can minimize the losses caused by fires.During the rescue processes,the travel time of fire trucks can be severely affected by traffic conditions,changing the effective coverage of fire stations.However,it is still challenging to determine the effective coverage of fire stations considering dynamic traffic conditions.This paper addresses this issue by combining the traveling time calculationmodelwith the effective coverage simulationmodel.In addition,it proposes a new index of total effective coverage area(TECA)based on the time-weighted average of the effective coverage area(ECA)to evaluate the urban fire services.It also selects China as the case study to validate the feasibility of the models,a fire station(FS-JX)in Changsha.FS-JX station and its surrounding 9,117 fire risk points are selected as the fire service supply and demand points,respectively.A total of 196 simulation scenarios throughout a consecutiveweek are analyzed.Eventually,1,933,815 sets of valid sample data are obtained.The results showed that the TECA of FS-JX is 3.27 km^(2),which is far below the standard requirement of 7.00 km^(2) due to the traffic conditions.The visualization results showed that three rivers around FS-JX interrupt the continuity of its effective coverage.The proposed method can provide data support to optimize the locations of fire stations by accurately and dynamically determining the effective coverage of fire stations.

Real-Time Monitoring of Meteorological Data at In-Situ GCW Remediation Sites

To optimize the self-organization network, self-adaptation, real-time monitoring, remote management capability, and equipment reuse level of the meteorological station supporting the portable groundwater circulation wells, and to provide real-time and effective technical services and environmental data support for groundwater remediation, a real-time monitoring system design of the meteorological station supporting the portable groundwater circulation wells based on the existing equipment is proposed. A variety of environmental element information is collected and transmitted to the embedded web server by the intelligent weather transmitter, and then processed by the algorithm and stored internally, displayed locally, and published on the web. The system monitoring algorithm and user interface are designed in the CNWSCADA development environment to realize real-time processing and analysis of environmental data and monitoring, control, management, and maintenance of the system status. The PLC-controlled photovoltaic power generating panels and lithium battery packs are in line with the concept of energy saving and emission reduction, and at the same time, as an emergency power supply to guarantee the safety of equipment and data when the utility power fails to meet the requirements. The experiment proves that the system has the characteristics of remote control, real-time interaction, simple station deployment, reliable operation, convenient maintenance, and green environment protection, which is conducive to improving the comprehensive utilization efficiency of various types of environmental information and providing reliable data support, theoretical basis and guidance suggestions for the research of groundwater remediation technology and its disciplines, and the research and development of the movable groundwater cycling well monitoring system.

Quality control of marine big data——a case study of real-time observation station data in Qingdao

Offshore waters provide resources for human beings,while on the other hand,threaten them because of marine disasters.Ocean stations are part of offshore observation networks,and the quality of their data is of great significance for exploiting and protecting the ocean.We used hourly mean wave height,temperature,and pressure real-time observation data taken in the Xiaomaidao station(in Qingdao,China)from June 1,2017,to May 31,2018,to explore the data quality using eight quality control methods,and to discriminate the most effective method for Xiaomaidao station.After using the eight quality control methods,the percentages of the mean wave height,temperature,and pressure data that passed the tests were 89.6%,88.3%,and 98.6%,respectively.With the marine disaster(wave alarm report)data,the values failed in the test mainly due to the influence of aging observation equipment and missing data transmissions.The mean wave height is often affected by dynamic marine disasters,so the continuity test method is not effective.The correlation test with other related parameters would be more useful for the mean wave height.

Study on Rear-end Real-time Data Quality Control Method of Regional Automatic Weather Station

[Objective] The aim was to study the rear-end real-time data quality control method of regional automatic weather station. [Method] The basic content and steps of rear-end real-time data quality control of regional automatic weather station were introduced. Each element was treated with systematic quality control procedure. The existence of rear-end real time data of regional meteorological station in Guangxi was expounded. Combining with relevant elements and linear changes, improvement based on traditional quality control method was made. By dint of evaluation and relevant check of element, the quality of temperature and pressure was controlled. [Result] The method was optimized based on traditional quality control method, and it narrowed the effectiveness of real-time data quality control. The quality check of hourly precipitation applied relevant check of hourly minimum temperature, vertical consistency check of radar data, which can effectively improve the accuracy and credibility of hourly precipitation quality control. [Conclusion] The method was on trial for one year in the quality control of real-time data in the regional automatic meteorological station in Guangxi and had gained good outcome.

Quality Control System of Meteorological Real-time Data from Automatic Weather Stations in Shandong

The quality control system for meteorological real-time data from automatic weather stations in Shandong realized integration of communi- cation system and provincial quality control system, and an interaction platform which was mainly created by Web was set up. The system not only was fully guaranteed for the funning of basic business, also improved the reliability of the data.

Planning and Real-time Pricing of EV Charging Stations Considering Social Welfare and Profitability Balance

This paper presents a planning and real-time pricing approach for EV charging stations(CSs).The approach takes the form of a bi-level model to fully consider the interest of both the government and EV charging station operators in the planning process.From the perspective of maximizing social welfare,the government acts as the decision-maker of the upper level that optimizes the charging price matrix,and uses it as a transfer variable to indirectly influence the decisions of the lower level operators.Then each operator at the lower level determines their scale according to the goal of maximizing their own revenue,and feeds the scale matrix back to the upper level.A Logit model is applied to predict the drivers’preference when selecting a CS.Furthermore,an improved particle swarm optimization(PSO)with the utilization of a penalty function is introduced to solve the nonlinear nonconvex bi-level model.The paper applies the proposed Bi-level planning model to a singlecenter small/medium-sized city with three scenarios to evaluate its performance,including the equipment utilization rate,payback period,traffic attraction ability,etc.The result verifies that the model performs very well in typical CS distribution scenarios with a reasonable station payback period(average 6.5 years),and relatively high equipment utilization rate,44.32%.

改进的灰色关联模型在水质评价中的应用

针对灰色关联模型在计算中存在的不足,对模型归一化矩阵的算法进行改进,扩大了模型的适用范围。将该模型运用到糯扎渡水电站库区施工前、后水质评价中,并与集对分析法进行对比,说明改进方法可行。计算结果表明施工期未对澜沧江水质产生明显影响,库区水质现阶段达标。

基于DS18B20的关联型温度检测系统的设计与实现

针对传统的温度检测系统对于通信基站测温点少、检测实时性和准确性较低的问题。设计了一种基于DS18B20温度传感器关联性模型的温度检测系统,通过建立不同位置测温值的关联模型,实现对温度异变信号的声光报警和自动处理等功能。该系统以DS18B20温度传感器为核心,设计了温度检测电路、数据关联电路、声光报警电路、继电器控制散热电路等模块。运行证明:本系统相对于传统的温度检测方法,系统的精确性和实时性都有明显改善,为通信基站的安全运行提供了可靠保障。

基于站点实时关联度的短时公交客流预测方法

为探究公交站点之间的关联度并对公交客流进行更精准的实时预测,本文提出基于Attention的交通预测核心算法(Traffic Forecast Model Based Attention,TFMA),结合数据预处理和站点信息编码完成基于站点实时关联度的短时公交客流预测方法。该方法首先创新性地提出了站点实时关联度,可实现对目标站点客流量更精准的预测;其次,在公交站点的编码信息中融入线路站点信息、客流变化率、天气、日期等关联因素;接着,该方法依靠Attention机制计算站点实时关联度;核心算法中使用multi-headed机制、增加通道和残差连接进一步提升预测能力;最后,以苏州市公交数据进行验证。结果显示:在准确率上,对比多元线性回归的53.8%、GRU(Gated Recurrent Unit)的66.9%和LightGBM(Light Gradient Boosting Machine)的81.2%,本文提出的基于站点实时关联度的短时公交客流预测方法的准确率在90%以上,表明该方法具备优秀的短时公交客流预测能力。

燃煤热水锅炉的运行节能

针对潍坊输油管理站燃煤热水锅炉运行效率低、能源消耗大的问题,通过分析过量空气系数、漏风、炉拱、炉排配风、堵灰以及炉膛负压等对锅炉热效率、出力和运行可靠性的影响,指出锅炉运行中应注意的各种问题,基于这些常见问题与热损失的关联度,提出了燃煤热水锅炉运行节能的若干途径。

多标签分类技术在移动通信基站选型中的研究

针对移动通信基站选型的问题,提出基于多标签分类技术移动通信基站选型的一种新方法。引入多标签分类技术中的BR方法,基于基站建设的历史数据进行自动选型,通过数据的分解、分类器的处理和集成,最后建立基站选型的预测模型。实验结果表明,多标签分类技术在移动通信基站建设中基站选型的预测上有较好的预测能力,优于传统的经验选型方法。

稀疏贝叶斯模型在跳频信号电台分选中的应用

当电磁环境更加复杂,现有的跳频信号分选算法,诸如K-Means聚类,支撑矢量机(SVM)等,往往面临较低的分选正确率或者较高的计算复杂度等问题。为了解决这两种问题,本文提出了一种基于稀疏贝叶斯学习(SBL)的跳频信号分选算法。在建立跳频信号分选模型之后,引入稀疏贝叶斯学习框架完成后续分选过程,并针对电磁环境中多个跳频电台的情况,建立了多电台跳频信号分选的结构模型。仿真实验环节验证了所提算法的有效性。

Fault-Tolerant Scheduling for Real-Time Embedded Control Systems

With the increasing complexity of industrial application, an embedded control system (ECS) requires processing a number of hard real-time tasks and needs fault-tolerance to assure high reliability. Considering the characteristics of real-time tasks in ECS, an integrated algorithm is proposed to schedule real-time tasks and to guarantee that all real-time tasks are completed before their deadlines even in the presence of faults. Based on the nonpreemptive critical-section protocol (NCSP), this paper analyzes the blocking time introduced by resource conflicts of relevancy tasks in fault-tolerant multiprocessor systems. An extended schedulability condition is presented to check the assignment feasibility of a given task to a processor. A primary/backup approach and on-line replacement of failed processors are used to tolerate processor failures. The analysis reveals that the integrated algorithm bounds the blocking time, requires limited overhead on the number of processors, and still assures good processor utilization. This is also demonstrated by simulation results. Both analysis and simulation show the effectiveness of the proposed algorithm in ECS.

大型铁路客运站候车层商业布局优化研究

随着出行选择的多样化,铁路旅客对商业服务需求的差异性逐步增大。大型铁路客运站商业设施规模不断扩大,对客运设备发挥其正常功能造成一定干扰,而合理的商业设施布局可以在保证铁路运输功能正常运行的同时,提高客运站商业服务水平。因此以提高大型客运站商业设施布局合理性为优化目标,将其分解为降低商业设施对旅客流线的干扰性、提高商业设施之间的相关性及减少旅客走行距离3个子目标,构建候车层商业设施布局优化模型。以天津站为例,介绍天津站候车层商业布局现状,通过求解0-1规划模型,得到并分析优化结果;并对优化前后的候车层旅客行为进行仿真研究,验证优化后布局方案的合理性。

PSO-RVM算法在地铁车站温控系统中的应用

鉴于地铁车站温度变化具有非线性、滞后性、时变性等特点,运用粒子群算法-关联向量机(PSO⁃RVM)算法建立地铁车站大系统温度控制模型。计算结果表明:相比于PSO⁃SVM算法,基于laplace核、r核、gauss核的PSO⁃RVM算法较适用于建立地铁车站大系统温度控制模型;此外,该算法也可进一步应用在地铁车站综合监控系统中。

基于灰色理论的水电站机组故障诊断

水电站机组设备故障诊断方法的研究,是水电站建设和正常运行维护的重要内容。针对大多数机组的机电设备都具有灰色系统的特征,且机组最常见的故障为电机断条、偏心等,在机组机电设备的故障诊断过程中引入灰色理论系统中灰关联故障诊断方法,对机组机电设备进行状态识别与故障诊断。充分论证了灰色关联故障分析法对诊断弱条件、少数据的水电站设备故障的有效性。

银盘—彭水区间流量与面雨量关系研究

本文以2011年6月以来彭水和银盘水电站流量及流域面雨量数据为基础资料,对银盘—彭水区间流量与面雨量变化关系进行了分析,并从该区间流量的形成规律出发,探寻对区间产流作用明显的影响因素,采用前一日区间流量、当日面雨量等预报因子建立分月的银盘—彭水日均区间流量预报模型。结果表明,利用回归模型求解,能够较为准确地预测区间产流的量级。

基于实测数据的阿克苏光伏电站相关性分析

光伏发电的不确定性、间歇性和波动性特征,会造成光伏发电弃光问题,掌握其特性是提高消纳的重要基础。本文基于实测数据分析光伏电站相关性。首先,给出了同一光伏电站不同时段出力的相关性和同一时段不同光伏电站出力的相关性计算方法;其次,从理论上分析云量因子和地理位置对于光伏电站出力相关性的影响;最后,以新疆阿克苏光伏电站为例,利用实测数据说明了云量因子和地理位置对同一光伏电站出力相关性的影响,以及不同光伏电站出力相关性的影响。

串联双调压室水电站多频振荡稳定性研究

建立了上游串联双调压室水电站的小波动稳定性分析模型,运用相关因子法得到系统的特征值和状态变量的相关关系,分析系统的振荡特性,并采用四阶龙格库塔法求解了系统振荡的时域过程.结果表明:通过相关因子法,可以对系统的特征值和状态变量的相关因子进行求解,得到影响系统低频、中频和高频振荡环节的主要因素;机组转速的时域过程存在多频振荡特性,且有主波与尾波之分,主波对应的是高频波,尾波表现为低频波和中频波的叠加;减小长引水隧洞的长度或者增大副调压室和主调压室的面积可以提高系统低频振荡环节的稳定性,减小短引水隧洞的长度和副调压室的面积或者增大主调压室的面积可以提高系统中频振荡环节的稳定性,增大调速器参数可以提高系统高频环节的稳定性.

基于灰色关联理论和BP神经网络的分布式光伏电站运维数据虚拟采集方法

由于分布式光伏电站的布置点多面广、分散无序,要实现其运维数据的全覆盖采集,最佳方式为每一个分布式光伏电站均配置一套数据采集装置,由此也将面临投资成本巨大、运维任务繁重等难题。为此,提出了一种基于灰色关联度和BP神经网络的分布式光伏电站数据虚拟采集方法,实现了在安装少量数据采集装置条件下完成对全区域内分布式光伏电站运维数据的采集。选取江苏某区域内分布式光伏电站为研究对象,先利用灰色关联理论分析该区域内安装数据采集装置的一个分布式光伏电站的历史运维数据,获知辐照度与分布式光伏出力的特征曲线;然后,将区域范围内待虚拟采集光伏站的日辐照度实时信息与历史辐照度数据进行关联度计算,并选取关联度达到0.9以上的历史日为相似日,然后基于相似日的历史数据建立BP神经网络数据虚拟采集模型,实现区域范围内分布式光伏电站数据的虚拟采集;最后,通过算例验证了该方法采集的光伏输出功率具有较高的精度,能够实现对网格化区域内光伏电站输出功率数据的虚拟采集。